Texas Instruments Machine Learning Research Engineer 

United States 

457186089

In this machine learning research engineer role, you’ll have the chance to work on the following topics:

• Explore the application of LLMs in code generation, evaluation, and optimization
• Conduct research and development on novel and efficient LLM architectures, training algorithms, and post-training algorithms
• Design and develop new reasoning models with domain-specific knowledge
• Design and implement advanced Agentic LLM system for complex task automations
• Collaborate with system teams and internal business teams to define and implement AI/ML solutions for core business

Minimum requirements:

• Doctoral degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, or related field
• 3 years of related experience

Preferred qualifications:

• Strong background in Natural Language Processing, Large Language Models, and Deep Learning frameworks
• Proven track record of designing, developing, and deploying machine learning models/LLMs that drive business value
• Proficiency in Python, C/C++, and software design, including debugging, performance analysis, and optimization
• Excellent understanding of LLM architectures and transformer-based models
• Experience with popular deep learning frameworks (e.g., PyTorch, JAX, ONNX) and LLM-specific libraries (e.g., transformers, trl, vllm)
• Strong foundation in text processing, tokenization, and embedding techniques
• Knowledge of few-shot learning, transfer learning, and fine-tuning
• Knowledge of LLM performance evaluation
• Knowledge of reinforcement learning for LLM; Experience with LLM post-training implementation, including PPO, DPO, and GRPO
• Experience with LLM agent implementation with tool calling
• Excellent communication and interpersonal skills, with the ability to work in a dynamic and distributed team